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作 者:危明[1] 李元香[1] 姜大志[1] 黄星焱[2]
机构地区:[1]武汉大学软件工程国家重点实验室,湖北武汉430072 [2]吉林大学计算机科学与技术学院,吉林长春130012
出 处:《武汉理工大学学报(信息与管理工程版)》2008年第4期514-518,共5页Journal of Wuhan University of Technology:Information & Management Engineering
基 金:国家自然科学基金资助项目(60473014;60773009);国家高科技术发展计划资助项目(2007AA01Z290)
摘 要:论述了反序-杂交算子在求解TSP上的优势,认为该算子算法结构简单,在求解问题时不仅速度快,而且有很好的精确性和稳定性。基于多父体杂交算法的精英子空间的方法在求解函数优化问题上可以得到很好的结果,将精英策略和反序-杂交算子相结合,来求解组合优化问题,在反序-杂交算法中运用精英策略进行个体选择,使算法具有更强的学习能力。数值实验表明,新算法比传统的反序-杂交算子具有更快的运行速度和更好的求解精度。TSP (Traveling Salesman Problem) is one of the typical NP- hard problems in combinational optimization. The advantages of Inver - over algorithm in solving TSP problems were discussed. With simple structure, this algorithm has a faster running speed and better accuracy and stability. Based on the Inver-over algorithm, the evolutionary algorithm is effective for solving combinational optimization problem, which owes much to the effective use of elite-policy. Combined with Inver-over algorithm, the elite policy can be used to solve the combinational optimization problem. Using the elite-policy to make individual selection in the Inver-over algorithm will make the algorithm full of learning ability. Numerical experiments show that the running-speed of the new algorithm is faster and more accurate than the old one.
分 类 号:TP311[自动化与计算机技术—计算机软件与理论]
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